# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.dm.dm_outport_bagging_fine_detail_dt import jms_dm__dm_outport_bagging_fine_detail_dt
from jms.dim.tab.dim_tab_pack_money_config_dt import jms_dim__dim_tab_pack_money_config_dt

jms_dm__dm_outport_bagging_fine_sum_dt = SparkSqlOperator(
    task_id='jms_dm__dm_outport_bagging_fine_sum_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(minutes=30),
    email=['matthew.xiong@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_outport_bagging_fine_sum_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_outport_bagging_fine_sum_dt/execute.hql',
    executor_memory='4G',
    executor_cores=4,
    num_executors=5,
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled' : 'true',  # 动态资源 Shuffle 服务开启
          #'spark.dynamicAllocation.maxExecutors'  : 100,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.maxExecutors'             : 10,
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.sql.sources.partitionOverwriteMode' : 'dynamic',  # 允许删改已存在的分区
        'spark.executor.memoryOverhead'  : '4G',  # 堆外内存
        'spark.sql.shuffle.partitions'  : 160,
        'spark.default.parallelism'  : 120,
        'spark.sql.auto.repartition' :'true'
    },
    hiveconf={
        'hive.exec.dynamic.partition': 'true',
        'hive.exec.dynamic.partition.mode': 'nonstrict',
        'hive.exec.max.dynamic.partitions.pernode': 200,
        'hive.exec.max.dynamic.partitions': 200
    },
    yarn_queue='pro',
)

jms_dm__dm_outport_bagging_fine_sum_dt << [
    jms_dm__dm_outport_bagging_fine_detail_dt, jms_dim__dim_tab_pack_money_config_dt
]



